Scholarly article on topic 'Quantitative assessment of the shelf life of ozonated apple juice'

Quantitative assessment of the shelf life of ozonated apple juice Academic research paper on "Agriculture, forestry, and fisheries"

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Academic research paper on topic "Quantitative assessment of the shelf life of ozonated apple juice"

Eur Food Res Technol (2011) 232:469-477 DOI 10.1007/s00217-010-1416-2

ORIGINAL PAPER

Quantitative assessment of the shelf life of ozonated apple juice

S. Patil • V. P. Valdramidis • B. K. Tiwari • P. J. Cullen • P. Bourke

December 2010/Published online: 6 January 2011

Received: 16 July 2010/Revised: 10 December 2010/Accepted: 20 © Springer-Verlag 2011

Abstract Sterile apple juice inoculated with S. cerevisiae ATCC 9763 (103 CFU/mL) was processed in a bubble column with gaseous ozone of flow rate of 0.12 L/min and concentration of 33-40 ig/mL for 8 min. The growth kinetics of S. cerevisiae as an indicator of juice spoilage was monitored at 4, 8, 12 and 16 °C for up to 30 days. The kinetics was quantitatively described by the primary model of Baranyi and Roberts, and the maximum specific growth rate was further modeled as a function of temperature by the Ratkowsky type model. The developed model was successfully validated for the microbial growth of control and ozonated samples during dynamic storage temperature of periodic changes from 4 to 16 °C. Two more characteristic parameters were also evaluated, the time of spoilage of the product under static temperature conditions and the temperature quotient, Q10. At lower static storage temperature (4 °C), no spoilage occurred either for unprocessed or ozone-processed apple juice. In the case of ozone-processed apple juice, the shelf life was increased when compared with the controls, and the Q10 was found to be 7.17, which appear much higher than that of the

S. Patil • P. J. Cullen • P. Bourke School of Food Science and Environmental Health, Dublin Institute of Technology, Cathal Brugha Street, Dublin 1, Ireland

V. P. Valdramidis (&)

Biosystems Engineering UCD School of Agriculture, Food Science and Veterinary Medicine University, College Dublin Belfield, Dublin 4, Ireland e-mail: vvaldram@gmail.com

B. K. Tiwari

Department of Food & Tourism Management, Manchester Metropolitan University, Manchester M14 6HR, UK

controls, indicating the effectiveness of ozonation for the extension of shelf life of apple juice.

Keywords Yeast • Ozone • Apple juice • Shelf life • Dynamic modeling

Introduction

Acidic products such as fruit juices contain substantial amounts of fermentable sugars. Spoilage of fruit and vegetable juices is primarily due to the proliferation of its natural acid-tolerant and osmophilic microflora [1]. Yeasts, lactic acid bacteria, and molds may account for the fermented taste, production of the carbon dioxide and the buttermilk off-flavor production, as well as the spoilage of juices [2]. Yeasts predominate in spoilage of acid food products as they have the ability to grow at low pH, high sugar concentration and low water activity conditions and resist inactivation by heat processing which enables them to survive or grow in fruit or fruit products [3, 4]. Fruit juices are generally rich in simple carbohydrates and complex nitrogen sources and hence are ideal substrates for yeasts. More than 110 species of yeasts have been listed as associated with food and food products, of which large proportions occur on fruits, and more than 40 are associated with soft drinks [5]. The contamination of fruit juices with yeasts is normally indicative of highly contaminated raw materials, failure in fruit juice pasteurization, in sanitation practices or the presence of preservative resistant yeasts [6].

Saccharomyces cerevisiae is one of the most important yeasts causing spoilage of fruit juices and soft drinks [5, 79] and can be considered as shelf life indicator [10, 11]. Several authors reported that fruit juice concentrates, fruit

pulps, packaged fruit juices and soft drinks are particularly prone to fermentative spoilage with S. cerevisiae, S. bay-anus and to a lesser extent S. pastoranious [4, 12-18]. Therefore, numerous heat inactivation studies have been conducted with S. cerevisiae because of its significance in the spoilage of heat-pasteurized fruit juices and carbonated beverages [8, 17, 19]. Fermentation of sugars such as glucose, fructose, and sucrose is the principal spoilage reaction of Saccharomyces species. Growth of yeasts is usually accompanied by formation of carbon dioxide and alcohol. Carbon dioxide gives the product a gassy, frothy appearance and causes a packaged product to swell and explode. In addition, the products develop a distinctive alcoholic, fermentative smell and taste [20]. Spoilage of fruit juice makes it unacceptable for human consumption.

Heat treatment is the most widely used method for preservation of fruit and vegetable juices due to its effectiveness in microbial inactivation [21] although it has certain disadvantages for nutritional and organoleptic values [22, 23]. There is consumer demand for a wider range of less heavily processed foods of improved quality with longer shelf life and negligible changes in the organoleptic and nutritional values. This has enhanced interest in non-thermal technologies which could be effective on the inactivation of the undesired microorganisms [24].

Alternatives to thermal pasteurization such as ozone treatment are under investigation for potential application in fruit juice preservation. Apple juice (or apple cider in North America) is one of these products which is consumed by people of all ages for its sensory and nutritional qualities. The FDA's approval of ozone as a direct additive to food in 2001 triggered interest in ozone applications development, and industry guidelines for apple juice and cider were published by the USFDA in 2004, which also highlighted gaps in the scientific knowledge [25].

Ozone is a powerful antimicrobial agent due to its potential oxidizing capacity and it appears to be active against bacteria, fungi, viruses, protozoa, as well as bacterial and fungal spores [26, 27]. Ozone destroys microorganisms by progressive oxidation of vital cellular components. Oxidation reactions are caused by either dissolved molecular ozone or free radical species formed during auto-decomposition of ozone [28]. Activated oxygen species resulting from ozone decomposition include singlet oxygen, hydroxyl radical, superoxide anion (perhydroxyl radical at low pH), and hydrogen peroxide which elicit potent cidal activity against a broad spectrum of microorganisms [29].

The objective of this study was to investigate the effect of ozone as a non-thermal treatment to extend the shelf life of an apple juice system. Modeling approaches that describe the growth dynamics of S. cerevisiae in previously inoculated ozone-processed apple juice under static (isothermal) and dynamic storage temperature conditions are

also developed in order to quantitatively assess the effect of ozonation on the shelf life of the product.

Materials and methods

Yeast strain and growth conditions

S. cerevisiae ATCC 9763 was obtained from microbiology stock culture of the School of Food Science and Environmental Health of the Dublin Institute of Technology, Dublin, Ireland. This strain was maintained as frozen stock at -70 °C in the form of protective beads (Technical Services Consultants Ltd, Lancashire, UK), which were plated onto potato dextrose agar (PDA, Scharlau Chemie, Barcelona, Spain) and incubated at 30 °C for 48 h to obtain single colonies before storage at 4 °C. Working cultures were prepared by inoculating a single colony into malt extract broth (MEB, Scharlau Chemie) and incubating at 30 °C for 24 h.

Apple juice inoculation

S. cerevisiae cells grown for 24 h were harvested by cen-trifugation (SIGMA 2K15, Bench Top Refrigerated Ultracentrifuge, AGB scientific Ltd) at 10,000 rpm for 10 min at 4 °C. The cell pellet was suspended in sterile phosphate buffered saline (PBS, Oxoid Ltd, UK) re-centrifuged twice as described earlier. Finally, after two washes with PBS, the cell pellet was re-suspended in PBS and the yeast density was determined by measuring absorbance at 550 nm using McFarland standard (BioMerieux, Marcy -l'Etoile, France).

Sterile, commercially prepared apple juice was obtained from a local retailer. This juice was chosen as a food system that could serve for performing controlled micro-bial experiments (e.g., [10, 30, 31]). The inoculum was then diluted in the juice to obtain approximately 106 CFU/ mL. For each investigation, the cell concentration was further diluted in apple juice to yield a final working concentration of 103 CFU/mL. The inoculated apple juice with S. cerevisiae sample was then processed with ozone.

Soluble solids content of untreated apple juice was measured using a hand-held refractometer (Bellingham and Stanley Ltd., UK). One drop of the juice was placed on the refractometer glass prism and soluble solid content was obtained as Brix. The measured °Brix was 11 ± 0.001. The pH of untreated product was measured using a pH meter with a glass electrode (Orion Model, England) and was 3.23 ± 0.015. Titratable acidity was determined by titrating 20 mL of the untreated apple juice sample diluted in 80 mL distilled water with 0.1 N NaOH using phenol-phthalein as an indicator. The volume of NaOH was converted to g malic acid per 100 mL of juice. The measured titratable acidity was 0.45 ± 0.009.

Ozone treatment

Ozone gas was generated using an ozone generator (Model OL8O, Ozone services, Canada, Fig. 1). Ozone was produced by a corona discharge generator. Pure oxygen was supplied via an oxygen cylinder (Air Products Ltd., Dublin, Ireland), and the flow rate was controlled using an oxygen flow regulator. Apple juice samples (90 mL) inoculated with S. cerevisiae (103 CFU/mL) were processed in a 100-mL ozone bubble column with a diameter of approximately 3.7 cm and height of around 21.7 cm. A previously determined optimum flow rate of 0.12 L/min [32] with an ozone concentration of 33-40 ig/ mL was applied for each treatment for 8 min at ambient temperature (15-18 °C) [33]. In that study, quality (color, phenolic content) and microbial parameters (E. coli strains ATCC 25922 and NCTC 12900) during ozone processing were assessed [33]. The ozone concentration was recorded using an ozone analyzer. Excess ozone was destroyed by an ozone destroyer unit. It should be mentioned that the apple juice contains large amount of organic matter which does not permit measurement of dissolved ozone in the liquid phase, but also there was not any residual ozone effects as all ozone not targeting on the microbial cells is consumed by the organic matter. All experiments were carried out in duplicate.

Storage study

Storage studies were performed for the following three types of samples. Apple juice inoculated with 103 CFU/mL

Fig. 1 Schematics of ozone processing equipment

served as an unprocessed control 1. The second sample was the ozonated apple juice. Subsequently, an unprocessed control 2 was prepared by inoculating S. cerevisiae cells with an inoculum level of 101 CFU/mL in order to start with a similar inoculum level that was attained after 8 min of ozone treatment.

Static storage temperature study (SST)

Unprocessed control samples of apple juice and ozone-processed apple juice samples (45 mL each) were stored at constant temperatures of 4, 8, 12, and 16 °C, respectively, in incubators (LMS cooled incubators, Lennox Laboratory Supplies, Dublin, Ireland) for a period up to 30 days. Aliquots of unprocessed and processed samples were taken daily for analysis.

Dynamic storage temperature study (DST)

For the DST study, unprocessed and processed apple juice samples were stored in an incubator where the lowest and the highest temperatures were set to 4 and 16 °C. The temperature was programmed to fluctuate according to a profile consisting of 4 °C for 12 h, followed by an increase of temperature from 4 to 16 °C and maintained at 16 °C for a further 12 h. The actual temperature profiles were recorded every 10 min using a temperature sensor connected to a data logger (Grant 1000 series Squirrel meter/ data logger, UK). This specific profile was chosen in order to create a scenario of temperature abuse enhancing the microbial growth on which the developed modeling approaches could be validated.

Microbiological analysis

Yeast populations were determined by plating onto PDA. Aliquots (1 mL) were withdrawn every day from ozone-processed and unprocessed juice stored at each different temperature, serially diluted in MRD, and 0.1 mL of appropriate dilutions was surface plated onto PDA in duplicate. Plates were incubated at 30 °C for 48 h and colony-forming units were counted. Results were reported as Log10CFU/mL.

Microbial modeling

Parameter identification under static conditions

S. cerevisiae growth data in ozone-processed apple juice stored under SST conditions were fitted to the explicit version of the Baranyi and Roberts [34] model (Eqs. 1-3). Regression was performed by using the DMFit Excel

add-in software, version 2.1(www.ifr.ac.uk/safety/DMFit). The model reads as follows

N (t)=N (0)+1max A(t)-ln 1 +

e1maxA(t) — 1

e(Nmax-N(0))

1 f e( 1maxt) + q(0)\

A(t) = t +-ln -

() imax V 1 + q(0) J

1 = ln

The kinetic parameters of maximum specific growth rate (lmax) (1/days), lag phase (k) (days), initial microbial population [N(0)] (Log10CFU/mL) and maximum population density (Nmax) (Log10CFU/ml) have then been estimated. q(0) (—) denotes the concentration of substance critical to the microbial growth and is related to the physiological state of the cells.

The maximum specific growth rates estimated under SST conditions were further modeled as a function of storage temperature by using the square root model [35, 36]:

i^max = b(T Tmin)

where b is a constant, T is the storage temperature (°C), Tmin is the theoretical minimum temperature for the growth of the organism. Eq. (4) has been used without the commonly applied square root transformation of the imax value. This required the performance of a non-linear regression which is available from the DMFit software. A (geometric) mean value for h0 = k * imaxfor each of the experimental set-ups (Control 1, Control 2, Ozonated) was estimated from the individual growth curves, considering that the parameter is constant, independent of the storage temperature [34, 37, 38] and the fact that the resulting ho was derived from the 3 levels of temperatures (refer to results). q(0) is related to the parameter h0 by the following equation [34]:

1 — e_h)

q(°)= —hT- • (5)

Model validation under dynamic storage temperature (DST) conditions

The validation of the yeast growth model was performed under DST conditions based on the time temperature profile of apple juice samples during storage (control and ozone-processed) in conjunction with the square root model Eq. (4). The predictions were performed with the differential equation of Baranyi and Roberts model [Eq. (6, 7)] in which the

Runge-Kutta method (ode23 s, Matlab, The Mathworks) was applied for the approximation of solutions of these ordinary differential equations:

dN (t) (jfrru-, „ ,2 \f q(t)

b(T (t)

■)2)

q(t) +1

(2) dq(t)

= (b(T(t) - Tmin)2) q(t).

(6) (7)

The root mean squared error (Eq. 8) [39] was used for evaluating the model fitting while the accuracy and the bias factors presented by Baranyi et al. [40] (Eqs. 9, 10) were considered in order to assess the prediction capability of the developed model.

(y expi y pre )

where yexpi are experimental observations, ypre are model predictions, nt are number of data points, and np are number of estimated model parameters.

Af= 10^

E log10 Ni - log Ni

E log10 Ni - log10 Ni

where log10Ni is the predicted microbial load and n is the number of the experimental measurements.

Calculation of the Q10 value

The temperature quotient (Q10) was also calculated from the information obtained in ''Parameter identification under static conditions'' section. Q10 shows the effect of temperature on the shelf life, and it is given as follows [41, 42]:

shelf life at T 0C

shelf life at (T + 10°C)'

Observe that this parameter was developed for a zero-order reaction when the influence of temperature on the reaction rate is described by using the Arrhenius relationship [43]. Nevertheless, this approach is proposed and applied for the current microbial kinetic study as an alternative method to assess the efficacy of the ozonated juice.

This Q10 value can be easily calculated by performing a regression between the ln shelf life (days) versus the temperature which yields a straight line. Consequently, Q10 = exp (10 k) with k the slope of the regression line.

The estimation of the time of the shelf life (ts) was calculated considering that a microbial level >106 CFU/mL resulted in a failure (spoilage) of the product (see for similar examples in other products: Al-Kadamany, et al. [44]). The shelf life time, ts, was obtained by solving Eq. (1-3) (solve command in Matlab, The Mathworks) for the estimated parameters of the two controls and the ozo-nated growth kinetics when log N(ts) = 6 log(CFU/mL).

Results

The growth of S. cerevisiae in unprocessed and ozone-processed apple juice was assessed at SST conditions from 4 to 16 °C. Representative growth curves of the yeast population are shown in Fig. 2. The initial inoculum of control 1 was similar to previously reported levels of 103 CFU/mL [30, 45], while this level has also been reported in sound apples [46]. Finally, Kisko et al. [47] recorded ca. 103 CFU/mL level of S. cerevisiae in unprocessed apple juice. In the case of the unprocessed control samples 1 and 2 (i.e., initial inoculum level of 3.0 and 1.30 log CFU/mL, respectively), the lag phase was not obvious when the juice was stored under high SST (12 and 16 °C) (Fig. 2a, b). However, a typical growth pattern of S. cerevisiae was observed in the ozone-processed apple juice stored under SST of 12 and 16 °C, consisting of an initial lag phase, an exponential growth phase followed by a stationary phase (Fig. 2c).

The estimated kinetic parameters and statistical indices resulting from the regression of the microbial data by the Baranyi and Roberts model are shown in Table 1. The values of imax and k varied according to the storage temperature. The imax of the unprocessed control samples increased from 0. 35 log CFU/day to 1.23 log CFU/day and for ozone-processed apple juice increased from 0.275 log CFU/day to 1.270 log CFU/day with increase of the temperature from 8 to 16 °C. However, the lag phase for ozone-processed apple juice was decreased from 15.07 days at 8 °C to 2.84 days at 16 °C. For both unprocessed and ozone-processed apple juice, the maximum population density (Nmax) was found to be unaffected when stored under high SST (12 and 16 °C). The effect of storage temperature on imax was further modeled as a function of temperature by using the secondary square root model. The estimated parameters of the model are shown in Table 2. The model described satisfactorily the effect of temperature on the growth of S. cerevisiae. The calculated value for the theoretical minimum temperature of growth in ozone-processed apple juice was 0.28 °C. The h0 values obtained for the static environments studied were 0.336, 0.671 and 3.417 for unprocessed control 1, unprocessed control 2 and ozone-processed apple juice samples, respectively.

J 2 1 0

0 3 6 9 12 15 18 21 24 27 30

0 3 6 9 12 15 18 21 24 27 30

Time (Days)

Fig. 2 Growth curves of Saccharomyces cerevisiae in unprocessed and ozone-processed apple juice stored at different static storage conditions (filled diamond 4 °C, filled triangle 8 °C, filled square 12 °C, filled circle 16 °C). a Unprocessed control 1. b Unprocessed control 2. c Ozone-processed

The model developed under SST conditions was validated under DST conditions by using a periodically changing temperature profile and performing predictions with Eq. (6, 7). As the maximum population density was independent of the applied storage temperature, it was fixed at 7.5 logs CFU/mL (average of Nmax estimated during isothermal conditions for which microbial stationary phase was reached). For the initial concentration N(0), a nominal value was taken from the measured plate count result, i.e.,

3.02 (for control 1), 1.32 (for control 2), 1.24 (for ozo-nated) log (CFU/mL). Finally, the nominal values for q(0) were 2.49, 1.05 and 0.03 for control 1, control 2 and ozonated apple juice, respectively, calculated using Eq. 5 and after estimation of the ho from the parameters derived under static environmental conditions. The comparison between the predicted and observed growth of S. cerevisiae in unprocessed apple juice and ozone-processed apple juice samples is shown in Fig. 3. The performance of the model was evaluated statistically by the calculation of the bias (Bf) and accuracy (Af) factors.

Two more characteristic parameters were evaluated, the Qi0 and the time of spoilage of the product under SST conditions (Fig. 4). At the lowest SST (4 °C), no spoilage occurred either for unprocessed or for ozone-processed apple juice. However, with the higher SSTs used, product spoilage was observed in 9.45, 3.78, and 2.35 days for unprocessed control 1 at 8, 12, and 16 °C, respectively. For unprocessed control 2, the spoilage occured after 15.08, 6.30, and 4.29 days at 8, 12, and 16 °C, respectively. In the case of ozone-processed apple juice, the shelf life was increased when compared with both types of controls and resulted in 34.26, 10.34, and 7.08 days at 8, 12, and 16 °C, respectively. Finally, the Qi0 was found to be 7.17 in the case of ozonated juice. This was much higher than that obtained for the controls, i.e., 5.68, 4.81, indicating the effectiveness of ozonation for extension of the shelf life of apple juice.

Discussion

Table 2 Parameters of the square root type model for the effect of temperature on the maximum specific growth rate of Saccharomyces cerevisiae

Sample type Parameter Estimated value RMSE

Unprocessed control-1 b 0.0043 ± 0.0011 0.093

Unprocessed control-1 Tmin ( C) -1.121 ± 0.0215

Unprocessed control-2 b 0.00276 ± 0.0010 0.088

Unprocessed control-2 Tmin ( C) -4.2439 ± 0.1455

Ozone-processed b 0.0052 ± 0.0010 0.033

Ozone-processed Tmin ( C) 0.2799 ± 0.00370

Fig. 3 Comparison between observed (points) and predicted (dotted lines) growth of Saccharomyces cerevisiae in unprocessed and ozone-processed apple juice under dynamic temperature conditions (filled circle unprocessed control 1, filled square unprocessed control 2, filled triangle ozone-processed)

The results of the present study showed that S. cerevisiae ATCC 9763 is able to grow in apple juice stored within a temperature range of 8-16 °C. The Baranyi and Roberts model as well as the square root model described the growth

of yeast populations in unprocessed and ozone-processed apple juice. Based on the static data, a new model was developed that described the growth of S. cerevisiae population well in unprocessed and ozone-processed apple

Table 1 Parameters of the Baranyi and Robert's model for the growth of Saccharomyces cerevisiae in unprocessed and ozone-processed apple juice under different static storage conditions

Temperature (°C) Sample type (imax) (1/days) (k) (days) N(0)(Log10 CFU/mL) Nmax (Logj0 CFU/mL) SE of fit RMSE

4 Unprocessed control 1 0.039 ± 0.003 8.48 ± 1.64 3.01 - 0.060 0.063

8 Unprocessed control-1 0.354 ± 0.010 - 2.91 7.43 ± 0.031 0.108 0.121

Unprocessed control-2 0.367 ± 0.008 1.10 ± 0.29 1.14 7.41 ± 0.025 0.069 0.075

Ozone-processed 0.275 ± 0.013 15.07 ± 0.55 0.95 - 0.156 0.175

12 Unprocessed control-1 0.846 ± 0.035 - 3.01 7.56 ± 0.029 0.104 0.094

Unprocessed control-2 0.798 ± 0.020 - 1.17 7.65 ± 0.041 0.127 0.116

Ozone-processed 0.762 ± 0.031 3.48 ± 0.214 1.01 7.51 ± 0.038 0.100 0.090

16 Unprocessed control-1 1.227 ± 0.085 - 3.32 7.56 ± 0.034 0.119 0.100

Unprocessed control-2 1.103 ± 0.033 - 1.47 7.66 ± 0.034 0.109 0.091

Ozone-processed 1.270 ± 0.104 2.84 ± 0.303 0.87 7.45 ± 0.060 0.165 0.137

3.5A 3-

8 12 16 Temperature (°C)

Fig. 4 Shelf life [ln(ts)] for unprocessed control (1 & 2) and ozone-processed apple juice samples (filled diamond unprocessed control 1, filled square unprocessed control 2, filled triangle ozone-processed at different storage temperatures tested

juice under dynamic conditions that simulated a storage temperature abuse. At the lower SSTs (4 and 8 °C), the longer lag phase indicates that the yeast population needed longer time to adapt to the environment. However, at higher storage temperatures, this effect was not evident, indicating the ability of yeasts to grow at these temperatures with a reduced or seemingly absent lag time. By comparison, in the case of ozone-processed apple juice stored at 8, 12 or 16 °C, the lag phase (k) was increased, indicating the effect of temperature and applied ozone stress on growth of S. cerevisiae populations. Panagou et al. [10] reported a very short lag phase in different pasteurized fruit juices even at the lowest storage temperatures, suggesting that inoculated yeasts' adaptation time was unaffected by these temperatures (4, 8, 12, and16 °C). However, in this study, a lag phase was observed for all ozone-processed samples. This could be due to the oxidizing action of the applied ozone treatment, which may exert additional stress prior to allowing growth. Ozone has been reported to inactivate cytosolic enzymes, with the most drastic inactivation for glyceraldehyde 3 phosphate dehydrogenase and to lesser extent to other cytosolic enzymes. It also affects the quantity of ATP and other nucleoside triphosphates, reducing to about 50% of its initial level [48].

The performance of the developed model was validated under dynamic conditions. Ross et al. [49] reported that predictive models should ideally have an Af and Bf = 1.00, indicating a perfect model fit where the predicted and actual response values are equal and satisfactory. Bf limits are more difficult to define because limits of acceptability are related to the specific application of the model. Ranges of 0.6-3.99 have been reported for the growth pathogen and spoilage microorganisms when compared with independent published data [49]. The values of Bf and Af indicated good agreement between observed data and predicted data points. Nevertheless, in the case of Control 2, some discrepancy was evident (Table 3). This could be

Table 3 Accuracy (Af) and bias (Bf) values between the predictions of the model tested

Control 1 1.9907 1.2227

Control 2 4.7422 2.4866

Ozonated 1.7575 1.0187

attributed to the effect of the inoculum size on the micro-bial adaptation phenomena. This observation may require further evaluation of the inoculum size effects which could elucidate if different values of h0 should be considered for each of the performed microbial predictions.

Different technologies have been applied for inhibiting the growth of spoilage microorganism in fruit juices. Pat-rignani et al. [30] evaluated the potential of high-pressure homogenization (HPH) for inactivation of S. cerevisiae 635 inoculated in apricot and carrot juice and its shelf life extension. Four or more repeated passes at 100 MPa of HPH to the apricot juice samples inoculated at a level of 3 log10 CFU/mL showed that S. cerevisiae population remained under the detection limit at least up to 144 h at 25 °C. For carrot juice samples subjected to five or more repeated HPH passes, the S. cerevisiae cell load was lower than 5 log10 CFU/mL after 144 h at 25 °C. However, refrigerated storage (4 °C) indicated satisfactory extension of shelf life of HPH processed juices. Qin et al. [50] reported over 3 weeks extension of standard shelf life of pulsed electric field (PEF)-processed apple juice when stored at 4 and 25 °C. Ferrentino et al. [51] concluded that high-pressure carbon dioxide (HPCD) treatment proved to be a promising alternative technique yielding juices with fresh-like characteristics and extension of shelf life with safety. Suarez-Jacobo et al. [52] reported the efficacy of ultra high pressure homogenization to develop fresh apple juice with an equivalent shelf life to pasteurized apple juice with respect to the microbiological characteristics. Vald-ramidis et al. [53] observed that no spoilage of apple juice was evident at storage temperatures of 4, 8, and 12 °C for 36 days after treatment with high hydrostatic pressure at 500 and 550 MPa. From the present work, it is evident that ozone is another non-thermal technology which can be employed for extending the shelf life of apple juice. The present results proved an increase in the shelf life of the ozonated product that varied between 2.79 and 24.81 days depending on the storage temperatures when compared with the control samples.

Validation of the developed modeling approaches will be expanded based on the suggestions by Pin et al. [54]. More specifically, kinetic data that come from competition of inoculated S. cerevisiae, pathogenic microorganism with a naturally occurring microflora of fresh apple juice will be incorporated in future model developments while

comparative studies between ozonated and other treated technologies will be applied. This will permit the application of this model to apple juice products with different properties. Further studies will focus on defining the failure (spoilage) of processed apple juice based on the effect of ozone on additional to previously reported quality parameters (e.g., color, phenolic content) [33] including volatiles responsible for flavor, odor and sensory evaluation. Effect of the different inoculums levels on the microbial adaptation phenomena will also be assessed to interpret possible modeling discrepancies.

Acknowledgments Funding for this research was provided under the National Development Plan 2000-2006, through the Food Institutional Research Measure, administered by the Department of Agriculture, Fisheries & Food, Ireland.

References

1. Tahiri I, Makhlouf J, Paquin P, Fliss I (2006) Inactivation of food spoilage bacteria and Escherichia coli O157:H7 in phosphate buffer and orange juice using dynamic high pressure. Food Res Int 39:98-105

2. Tournas VH, Heeres J, Burgess L (2006) Moulds and yeasts in fruit salads and fruit juices. Food Microbiol 23:684-688

3. Put HMC, De Jong J (1980) The heat resistance of selected yeast causing spoilage of canned soft drinks and fruit products. In: Skinner FA, Passmore SM, Davenport RR (eds) Biology and activities of yeasts. Academic Press, London

4. Stratford M, Hofman PD, Cole MB (2000) Fruit juice, fruit drinks and soft drinks. In: Lund BM, Baird-Parker TC, Gould GW (eds) The microbiological safety and quality of food. Aspen publishers, Gaithersberg, MD, pp 836-869

5. Barnett JA, Payne RW, Yarrow D (2000) Yeast characteristics and identification, 3rd edn. Cambridge University Press, Cambridge

6. Lima Tribst AA, de Souza Sant'Ana A, de Massaguer PR (2009) Review: microbiological quality and safety of fruit juices- past, present and future perspectives. Crit Rev Microbiol 35(4):310-339

7. Deak T, Beuchat LR (1996) Handbook of food spoilage yeasts. CRC press, Boca Raton FL

8. Fleet GH (1992) Spoilage yeasts. Crit Rev Biotechnol 12:1-44

9. Pitt JI, Hocking AD (1997) Fungi and food spoilage, 2nd edn. Aspen Publishers, Gaithersburg, MD

10. Panagou EZ, Karathanassi S, Le Marc Y, Nychas GJE (2009) Development of a product specific model for spoilage of pasteurized fruit juices by Saccharomyces cerevisiae and validation under dynamic temperature conditions. Predictive Modelling Foods. 8-12 Sept, Washington DC, USA, (CDROM)

11. Valverde MT, Marin-Iniesta F, Calvo L (2010) Inactivation of Saccharomyces cerevisiae in conference pear with high pressure carbon dioxide and effects on pear quality. J Food Eng 98: 421-428

12. Arias CR, Burns JK, Friedrich LM, Goodrich RH, Parish ME (2002) Yeast species associated with orange juice: evaluation of identification methods. Appl Environ Microbiol 68:1955-1961

13. Deak T, Beuchat LR (1993) Yeasts associated with fruit juice concentrates. J Food Prot 56:777-782

14. Deak T, Beuchat LR (1993) Comparison of SIM API 20C and ID32C systems for identification of yeasts from fruit juice concentrates and beverages. J Food Prot 56:585-592

15. Las Heras-Vazquez FJL, Mingorance-Cazorla L, Clemente-Jimenez JF, Rodriguez-Vico F (2003) Identification of yeast species from orange fruit and juice by RFLP and sequence analysis of the 58S r RNA gene and two internal transcribed spacers. FEMS Yeast Res 3:3-9

16. Sancho T, Gimenez-Jurado G, Malfeito-Ferreira M, Loureiro V (2000) Zymological indicators: a new concept applied to the detection of potential spoilage yeast species associated with fruit pulps and concentrates. Food Microbiol 17:613-624

17. Thomas S (1993) Yeasts as spoilage organisms in beverages. In: Rose AH, Harrison JS (eds) The yeasts. vol. 5, 2nd edn. Academic press, London, pp 517-561

18. Torok T, King AD (1991) Comparative study on the identification of foodborne yeasts. Appl Environ Microbiol 57:1207-1212

19. Stratford M, James SA (2003) Non-alcoholic beverages and yeasts. In: Boekhout T, Robert V (eds) Yeasts in food: beneficial and detrimental aspects. Behr's-Verlag, Germany, pp 309-345

20. Fleet GH (2006) Saccharomyces and related genera. In: de Clive Blackburn W (ed) Food spoilage microorganisms. CRC press, England, pp 306-335

21. Tribst AAL, Franchi MA, Cristianini M (2008) Ultra-high pressure homogenization treatment combined with lysozyme for controlling Lactobacillus brevis contamination in model system. Innov Food Sci Emerg Technol 9:265-271

22. Pathanibul P, Taylor TM, Davidson PM, Harte F (2009) Inacti-vation of Escherichia coli and Listeria innocua in apple and carrot juices using high pressure homogenization and nisin. Int J Food Microbiol 129:316-320

23. Vachon JF, Kheadr EE, Giasson J, Paquin P, Fliss I (2002) Inactivation of food borne pathogens in milk using dynamic high pressure. J Food Prot 65:345-352

24. Diels AMJ, Callewaert L, Wuytack EY, Masschalck B, Michiels CW (2005) Inactivation of Escherichia coli by high-pressure homogenisation is influenced by fluid viscosity but not by water activity and product composition. Int J Food Microbiol 101:281-291

25. US Food and Drug Administration (USFDA) (2004) FDA Guidance to industry, 2004: recommendations to processors of apple juice or cider on the use of ozone for pathogen reduction purposes. Available online: http://www.fda.gov/Food/Guidance ComplianceRegulatoryInformation/GuidanceDocuments/Juice/ ucm072524.htm (Accessed 5 July 2010)

26. Khadre MA, Yousef AE, Kim JG (2001) Microbiological aspects of ozone applications in food: a review. J Food Sci 66(9): 1241-1252

27. Cullen PJ, Valdramidis VP, Tiwari BK, Patil S, Bourke P, O'Donnell CP (2010) Ozone processing for food preservation: an overview on fruit juice treatments. Ozone: Sci Eng 32(3): 166-179

28. Hunt NK, Marinas BJ (1997) Kinetics of Escherichia coli inactivation with ozone. Water Res 31:1355-1362

29. Korycka-Dahl M, Richardson T (1978) Activated oxygen species and oxidation of food constituents. Crit Rev Food Sci Nutr 10:209-241

30. Patrignani F, Vannini L, Kamdem SLS, Lanciotti R, Guerzoni ME (2009) Effect of high pressure homogenization on Saccha-romyces cerevisiae inactivation and physico-chemical features in apricot and carrot juices. Int J Food Microbiol 136(1):26-31

31. Mosqueda-Melgar J, Raybaudi-Massilia RM, Martin-Belloso O (2008) Combination of high-intensity pulsed electric fields with natural antimicrobials to inactivate pathogenic microorganisms and extend the shelf-life of melon and watermelon juices. Food Microbiol 25:479-491

32. Patil S, Cullen PJ, Kelly B, Frias JM, Bourke P (2009) Extrinsic control parameters for ozone inactivation of Escherichia coli using ozone bubble column. J Appl Microbiol 107(3):830-837

33. Patil S, Torres B, Tiwari BK, Wijngaard HH, Bourke P, Cullen PJ, O'Donnell CP, Valdarmidis VP (2010) Safety and quality assessment during the ozonation of cloudy apple juice. J Food Sci 75(7):M437-M443

34. Baranyi J, Roberts TA (1994) A dynamic approach to predicting bacterial growth in food. Int J Food Microbiol 23:277-294

35. Ratkowsky DA, Olley J, McMeekin TA, Ball A (1982) Relationship between temperature and growth-rate of bacterial cultures. J Bacteriol 149:1-5

36. Ratkowsky DA, Lowry RK, McMeekin TA, Stokes AN, Chandler RE (1983) Model for bacterial cultures growth rate throughout the entire biokinetic temperature range. J Bacteriol 154:12221226

37. Fu B, Taoukis PS, Labuza TP (1991) Predictive microbiology for monitoring spoilage of dairy products with time-temperature indicators. J Food Sci 56:1209-1215

38. Le Marc Y, Valik L, Medved'ova A (2009) Modelling the effect of the starting culture on the growth of Staphylococcus aureus in milk. Int J Food Microbiol 129:306-311

39. Neter, Wasserman, Whitmore (1992) Applied statistics, 4th edn. Prentice hall, Englewood cliffs, NJ, pp 1-989

40. Baranyi J, Pin C, Ross T (1999) Validating and comparing predictive models. Int J Food Microbiol 48:159-166

41. Duyvesteyn WS, Shimoni E, Labuza TP (2001) Determination of end of shelf-life for milk using Weibull hazard method. Lebensm Wiss Technol 34:143-148

42. Labuza TP (1982) Shelf-life dating of foods. Food and Nutrition Press Inc, Westport, Connecticut, pp 54-58, 223

43. Man D, Jones (2000) Shelf-life evaluation of foods. In: Singh RP (ed) Scientific principles of shelf-life evaluation. Aspen Publication, Gaithersburg, Maryland

44. Al-kadamany E, Toufelli I, Khattar M, Abou-Jawdeh Y, Harakeh S, Haddad T (2002) Determination of shelf life of concentrated yogurt (Labneh) produced by in-bag straining of set yogurt using hazard analysis. J Dairy Sci 85:1023-1030

45. Thomas LV, Ingrama RE, Yub S, Delves-Broughtona J (2004) Investigation of the effectiveness of Ascopyrone P as a food preservative. Int J Food Microbiol 93:319-323

46. Brackett RE (1994) Microbiological spoilage and pathogens in minimally processed refrigerated fruits and vegetables. In: Wiley RC (ed) Minimally processed refrigerated fruits and vegetables. Chapman & Hall, New York, London, pp 269-312

47. Kisko G, Sharp R, Roller S (2005) Chitosan inactivates spoilage yeasts but enhances survival of Escherichia coli O157:H7 in apple juice. J Appl Microbiol 98:872-880

48. Hinze H, Prakash D, Holzer H (1987) Effect of ozone on ATP, cytosolic enzymes and permeability of Saccharomyces cerevisiae. Arch Microbiol 147:105-108

49. Ross T, Dalgaard P, Tienungoon S (2000) Predictive modeling of the growth and survival of Listeria in fishery products. Int J Food Microbiol 62:231-245

50. Qin BL, Chang FJ, Barbosa-Canovas GV, Swanson BG (1995) Nonthermal inactivation of Saccharomyces cerevisiae in apple juice using pulsed electric fields. Lebensmm Wiss Technol 28:564-568

51. Ferrentino G, Bruno M, Ferrari G, Poletto M, Balaban MO (2009) Microbial inactivation and shelf life of apple juice treated with high pressure carbon dioxide. J Biol Eng 3:3

52. Suarez-Jacobo A, Gervilla R, Guamis B, Roig-Sagues AX, Saldo J (2009) Effect of UHPH on indigenous microbiota of apple juice: a preliminary study of microbial shelf life. Int J Food Microbiol 136(3):261-267

53. Valdramidis VP, Graham WD, Beattie A, Linton M, McKay A, Fearon AM, Patterson MF (2009) Defining the stability interfaces of apple juice: implications on the optimisation and design of high hydrostatic pressure treatment. Innov Food Sci Emerg Technol 10(4):396-404

54. Pin C, Sutherland JP, Baranyi J (1999) Validating predictive models of food spoilage organisms. J Appl Microbiol 87:491-499